The imaging and analysis of features on a substrate is an important task in various technical applications. For example in biochemical analysis it is a common technique to apply small spots of a carrier substance on a substrate according to a predefined pattern. Subsequently, small quantities of different cell materials are added to the spots of the carrier substance and cell growth of the different spots is monitored as a function of time by taking images of the spots on the substrate after certain periods of time and by analyzing features within the images.
The imaging of the features can be facilitated by arranging them on the substrate according to a predefined pattern. Usually, dedicated scanner hardware is used to perform the scanning and the substrate is scanned only at the predefined known positions of the spots registered during the preparation of the substrate in annotation files. This common technique is limited in several aspects.
Depending on the number of features on the substrate the scanning of the entire substrate requires a large number of single scans involving a corresponding large number of repeated and very precise mechanic displacements performed by the scanning apparatus for moving the substrate in front of the scanner or the scanner relative to the substrate. In biochemical applications substrates may contain more than 3888 features on a single substrate requiring a corresponding number of mechanical displacement steps. Accordingly, the scanning requires a highly precise and correspondingly expensive hardware.
Furthermore, the scanning process depends strongly on the precise information about the position of the spots on the substrate. The scanning may fail in case of a lack of precise positioning data or in case of a misalignment between the scanner and the substrate.
In view of these shortcomings, there is a need for an improved method and a corresponding apparatus that allows a faster imaging of features on a substrate and a reduction of the demands on the imaging hardware, in particular, in cases of substrates containing a large number of features.